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Introduction to Databases

From Biological to Spatio-Temporal

By Peter Revesz

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Unique and reader-friendly, Introduction to Databases provides a comprehensive overview of the database field. Numerous database systems are discussed, enabling readers to begin to develop their own complex database research and applications.

Full Description

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  • ISBN13: 978-1-8499-6094-6
  • 772 Pages
  • User Level: Students
  • Publication Date: December 12, 2009
  • Available eBook Formats: PDF
Full Description
This textbook reveals the workings of numerous database systems, enabling readers to develop complex database applications. Students will gain hands-on experience by following the exercises. The theory is complemented by detailed examination of specific applications from a broad range of areas. The text assumes only basic discrete mathematics, linear algebra, and programming knowledge. Features: Provides descriptions of 11 types of databases, and 2 database systems; Concludes each chapter with bibliographic notes and exercises; Examines database design, including issues of database interoperability, data integration, interpolation and approximation, and prediction and data mining; Presents course aids at a supporting website; Covers topics on indexing methods, data visualization, the safety of queries, general evaluation algorithms, the efficient implementation of evaluation algorithms, and the complexity of the evaluation of different types of queries; Structured to allow for flexible course design.
Table of Contents

Table of Contents

  1. Data Models, Queries, Evaluation.
  2. Propositional Databases.
  3. Relational Databases.
  4. Constraint Databases.
  5. Temporal Databases.
  6. Geographic Databases.
  7. Moving Objects Databases.
  8. Image Databases.
  9. Constraint Objects Databases.
  10. Genome Databases.
  11. Set Databases.
  12. Constraint Deductive Databases.
  13. The MLPQ System.
  14. The DISCO System.
  15. Database Design.
  16. Interoperability.
  17. Data Integration.
  18. Interpolation and Approximation.
  19. Prediction and Data Mining.
  20. Indexing.
  21. Data Visualization.
  22. Safe Query Languages.
  23. Evaluation of Queries.
  24. Implementation Methods.
  25. Computational Complexity.
  26. Software Verification.

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